Digital measurement is a business function where companies collect information about how users perform certain activities on webpages or otherwise interact with published web content. These users may be referred to as digital content consumers. Companies that publish web content, known as digital content providers, have an interest in understanding what and how their content is consumed by collecting usage statistics from the digital content consumers. Digital measurement based on the gathered usage statistics can provide insight about customers, thereby improving a company's decision making in areas such as targeted marketing, product testing, user analysis (e.g., pattern identification) and business model improvement. Exemplary usage statistics collected in digital measurement include consumer operations such as page access, link clicking, file downloading, completing a transaction, exiting a page, etc. Workflows for consumer activities can also be collected and analyzed to track common usage patterns among different consumer groups.
To collect usage statistics, webpages are pre-loaded with one or more descriptive tags. When a user accesses a webpage, the webpage asks its web server for associated tags describing the page. After obtaining the tag information from the web server, the webpage sends the tagged data to a data collection center for recordation and tracking. Generally, this type of tracking provides feedback to a company on how their webpages are used. As an example, a webpage associated with a financial institution can provide information about 529 college savings plans and the corresponding tag can include the following keywords describing the webpage:                <meta name=“page description” keywords=“529 plans, 529 college savings plans, 529 college savings plans, college savings plans, saving for college, college savings, 529 tax, 529 plan application, 529 savings plan, college 529”>For measurement purposes, the topic of the page corresponding to the keywords in the tag is provided as follows:        Page topic=Financial Planning|Investing Strategies|529 planWhen the webpage is accessed, a measurement mechanism can maintain a running total of user interests in the topics corresponding to the tag and increase this total by one with each access. If this is the only webpage across the company's web site about 529 plans and the page is accessed 10,000 times during a given day, the data in the data collection center can show that the topic “529 plans” has been viewed 10,000 times. Therefore, by analyzing the usage metrics (e.g., page accesses) across the entire web site, a measurement mechanism is able to determine which topics are of interest to the consumers.        
To ensure that the collected data accurately describes consumer activities with respect to a webpage, tags associated with the webpage need to correctly represent the page content. Tags that are initially reviewed and deemed to be accurate can lose their accuracy over time if they are not updated when significant modifications occur to the webpage. If a tag no longer reflects the content of the webpage, this can affect the validity of the resulting data collected and invalidate further analytics based on the collected data. Invalid data can result in incorrect business decisions being made, such as management focusing on the wrong business priorities, a supply chain department maintaining the wrong inventories, or a marketing department running a marketing campaign of little consumer interest. Therefore, data provided by digital measurement needs to accurately capture actual consumer behavior.
Webpage owners can choose to manually update tags associated with a page when the page is edited. However, in cases where the content of a webpage can be changed by many different groups within a company, constantly reviewing the tags of a page to ensure that they are accurate is not only time and resource intensive, but also error-prone. There is a lack of system on today's market that can provide automated tag review and update to solve this problem.